Cingulotomy for Psychiatric Disease: Microelectrode Guidance, a Callosal Reference System for Documenting Lesion Location, and Clinical Results
Bibliographic record
Abstract
OBJECTIVE: To evaluate magnetic resonance imaging (MRI)- and microelectrode recording-guided cingulotomy for patients with psychiatric disorders and to develop a new method of mapping lesion location in anterior cingulate cortex that takes into account the significant interindividual variability in callosal morphometry. METHODS: MRI and microelectrode recording were used to guide placement of radiofrequency lesions in patients with obsessive-compulsive disorder (n = 21) or affective disorders (n = 5). Postoperative improvement was evaluated with the Yale-Brown Obsessive-Compulsive Scale in 15 of the 21 obsessive-compulsive disorder patients studied. From the postoperative MRI scans, we developed a coordinate system for position in the anterior cingulate cortex. The callosal line passes from the most anterior point of the corpus callosum (c = 0) to the most posterior (c = 100). We reconstructed the lesions onto a sagittal map from the Talairach and Tournoux atlas using the distance along the callosal line and the distance above the upper surface of the corpus callosum. RESULTS: The location of neuronal activity distinguished gray and white matter and was useful in delineating the upper and lower cortical banks of the cingulate gyrus, the cingulate bundle, and the corpus callosum. This information was used to place the lesions. Lesions typically were 6 to 8 mm in diameter on T2-weighted MRI scans. The inferior margins were along the corpus callosum from c = 16 to c = 38. Four of 15 patients with obsessive-compulsive disorder had a documented decrease of more than 35% on the Yale-Brown Obsessive-Compulsive Scale, but only one patient had a sustained benefit for more than 1 year. CONCLUSION: Microelectrode recording is useful for lesion placement. Our system for reporting location in anterior cingulate cortex normalizes for differences in callosal morphometry. These techniques may aid future study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".